Fault Identification for Transformer Axial Winding Displacement Using Nanosecond IFRA and SFRA Experiments

被引:1
|
作者
Huang, J. J. [1 ]
Tang, W. H. [1 ]
Xin, Y. L. [1 ]
Zhou, J. J. [1 ]
Wu, Q. H. [1 ]
机构
[1] South China Univ Technol, Sch Elect Power Engn, Guangzhou 510641, Guangdong, Peoples R China
关键词
FREQUENCY-RESPONSE; DEFORMATION; TRENDS;
D O I
10.1088/1757-899X/366/1/012067
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Nanosecond IFRA has the potential to realize online detection of power transformer winding deformation and displacement. But this method is not mature even in offline condition, and the reliability, accuracy and repeat ability of which are in doubt. To verify the reliability and accuracy of nanosecond IFRA a comparison experiment is conducted between it and a mature method which is applied widely all over the world, SFRA. In this experiment, three levels of axial displacements are experimentally simulated on a dry-type distribution transformer in the lab and both a nanosecond IFRA system and a commercial SFRA analyser are applied to obtain the frequency responses at each fault level separately. To verify the repeatability of Nanosecond IFRA, two Nanosecond IFRA measurements conducted in a time interval of 30 days with all the test condition remaining the same are compared. The results are analysed by visual inspection and quantitative comparison.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Fault Identification of Winding Axial Displacement and Inter-turn Short Circuit for UHVDC Transformer
    Yu, Bin
    Wang, Tongwen
    Xie, Min
    Jiang, Feng
    Liu, Xiaohui
    Xiao, Huafeng
    [J]. 2022 4TH INTERNATIONAL CONFERENCE ON SMART POWER & INTERNET ENERGY SYSTEMS, SPIES, 2022, : 378 - 383
  • [2] Location of Faults in Transformer Winding using SFRA
    Usha, K.
    Joseph, Jineeth
    Usa, S.
    [J]. 2013 IEEE 1ST INTERNATIONAL CONFERENCE ON CONDITION ASSESSMENT TECHNIQUES IN ELECTRICAL SYSTEMS (CATCON), 2013, : 196 - 201
  • [3] Identification of Power Transformer Winding Mechanical Fault Types Based on Online IFRA by Support Vector Machine
    Zhao, Zhongyong
    Tang, Chao
    Zhou, Qu
    Xu, Lingna
    Gui, Yingang
    Yao, Chenguo
    [J]. ENERGIES, 2017, 10 (12)
  • [4] Improved Power Transformer Winding Fault Detection using FRA Diagnostics - Part 1: Axial Displacement Simulation
    Hashemnia, Naser
    Abu-Siada, A.
    Islam, S.
    [J]. IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION, 2015, 22 (01) : 556 - 563
  • [5] Inter Disc Fault Location in Transformer Windings Using SFRA
    Usha, K.
    Usa, S.
    [J]. IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION, 2015, 22 (06) : 3567 - 3573
  • [6] Investigating the Effect of Axial Displacement of Transformer Winding on the Electromagnetic Forces
    Dawood, Kamran
    Komurgoz, Guven
    Isik, Fatih
    [J]. 2020 7TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ICEEE 2020), 2020, : 360 - 364
  • [7] General Diagnosis of Transformer Winding Axial Displacement Faults Based on FEM Simulation and On-site Experiments
    Lu, Fei
    Jin, Lei
    Liu, Siwei
    Liu, Yi
    Li, Hua
    Lin, Fuchang
    [J]. 2016 IEEE ELECTRICAL INSULATION CONFERENCE (EIC), 2016, : 223 - 228
  • [8] An Efficient Method to Localize and Quantify Axial Displacement in Transformer Winding Using Support Vector Machines
    Muhammed, A.
    Saji, P.
    Mojiza, J.
    Vinod, V.
    Kumar, Sunil P. R.
    [J]. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2024, 60 (01) : 1827 - 1836
  • [9] On-Line Monitoring of Transformer Winding Axial Displacement Using UWB Sensors and Neural Network
    Mokhtari, G.
    Gharehpetian, G. B.
    Faraji-Dana, R.
    Hejazi, M. A.
    [J]. INTERNATIONAL REVIEW OF ELECTRICAL ENGINEERING-IREE, 2010, 5 (05): : 2122 - 2128
  • [10] Determination of transformer HV winding axial displacement extent using hyperbolic method - a feasibility study
    Rahbarimagham, Hesam
    Karami, Hossein
    Esmaeili, Saeid
    Gharehpetian, Gevork B.
    [J]. IET ELECTRIC POWER APPLICATIONS, 2019, 13 (07) : 1004 - 1013